Project Summary Evidence has demonstrated that 20-hydroxyeicosatetraenoic acid (20-HETE) is a key microvascular constrictive regulator and is formed by the omega-oxidation of arachidonic acid (AA) by the cytochrome P450 4 (CYP4) family. We and others have pre-clinically demonstrated that inhibition of 20-HETE formation is neuroprotective in both stroke and the cardiac arrest (CA) rat models of pediatric and adult brain injury. Also, in the clinical setting, we have shown that 20-HETE levels in the cerebrospinal fluid of subarachnoid hemorrhage (SAH) patients are associated with a >3-fold increase in mortality and a >2-fold increase in poor outcomes post-insult. All available preclinical and clinical evidence suggest that acute interventions that aim to inhibit 20- HETE formation hold great promise in the treatment of post-injury brain hypoperfusion after neurovascular brain injury. Despite the promise a 20-HETE formation (CYP4) inhibitor holds as a neurpotectant, there is no such inhibitor available for clinical use. A small number of the 20-HETE formation (CYP4) inhibitors have been reported in the literature. Unfortunately however, all compounds disclosed have shortcomings that impede their successful advancement to the clinic. Through rational drug design and computational methods we have identified a lead series, exemplified by the UPMP00010 scaffold. Compounds from this series have excellent potency and physicochemical properties appropriate for CNS-acting agents. Compounds from this series also have good solubility, high blood brain barrier (BBB) permeability potential and importantly, high metabolic stability when compared to leading literature inhibitors. In the proposed work, we aim to optimize further the UPMP00010 scaffold, and our advanced lead UPMP00022, to identify preclinical lead compounds to be tested in vivo for neuroprotection in the pediatric (PND17) asphyxial CA rat model of brain injury. We propose a multi- dimensional optimization approach to identify preclinical CYP4 inhibitors that may have clinical potential. In the R21 phase of the proposed work, we will harness rational drug design, computational and medicinal chemistry, cheminformatics, in vitro assays and a decision making algorithm/workflow to identify preclinical leads that have suitable characteristics (potency, selectivity, physicochemical properties) for testing in vivo. In the R21 phase we will evaluate our two best preclinical leads in vivo for pharmacokinetics and target engagement in order to select the best preclinical lead for a rigorous efficacy study that will be conducted during the R33 phase of the proposed work. In the R33 phase, we will rigorously evaluate cerebral blood flow (CBF), neuronal degeneration and neurological outcomes for assessing efficacy.